Real-time dense simultaneous localization and mapping using monocular cameras
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2017
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| Online Access: | http://hdl.handle.net/1721.1/107051 |
| _version_ | 1826204564117782528 |
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| author | Greene, W. Nicholas (William Nicholas) |
| author2 | Nicholas Roy and Ted J. Steiner. |
| author_facet | Nicholas Roy and Ted J. Steiner. Greene, W. Nicholas (William Nicholas) |
| author_sort | Greene, W. Nicholas (William Nicholas) |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016. |
| first_indexed | 2024-09-23T12:57:28Z |
| format | Thesis |
| id | mit-1721.1/107051 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:57:28Z |
| publishDate | 2017 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1070512019-04-10T15:48:55Z Real-time dense simultaneous localization and mapping using monocular cameras Greene, W. Nicholas (William Nicholas) Nicholas Roy and Ted J. Steiner. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Aeronautics and Astronautics. Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 91-100). Cameras are powerful sensors for robotic navigation as they provide high-resolution environment information (color, shape, texture, etc.), while being lightweight, low-power, and inexpensive. Exploiting such sensor data for navigation tasks typically falls into the realm of monocular simultaneous localization and mapping (SLAM), where both the robot's pose and a map of the environment are estimated concurrently from the imagery produced by a single camera mounted on the robot. This thesis presents a monocular SLAM solution capable of reconstructing dense 3D geometry online without the aid of a graphics processing unit (GPU). The key contribution is a multi-resolution depth estimation and spatial smoothing process that exploits the correlation between low-texture image regions and simple planar structure to adaptively scale the complexity of the generated keyframe depthmaps to the quality of the input imagery. High-texture image regions are represented at higher resolutions to capture fine detail, while low-texture regions are represented at coarser resolutions for smooth surfaces. This approach allows for significant computational savings while simultaneously increasing reconstruction density and quality when compared to the state-of-the-art. Preliminary qualitative results are also presented for an adaptive meshing technique that generates dense reconstructions using only the pixels necessary to represent the scene geometry, which further reduces the computational requirements for fully dense reconstructions. by W. Nicholas Greene. S.M. 2017-02-22T19:01:14Z 2017-02-22T19:01:14Z 2016 2016 Thesis http://hdl.handle.net/1721.1/107051 971021875 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 100 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Aeronautics and Astronautics. Greene, W. Nicholas (William Nicholas) Real-time dense simultaneous localization and mapping using monocular cameras |
| title | Real-time dense simultaneous localization and mapping using monocular cameras |
| title_full | Real-time dense simultaneous localization and mapping using monocular cameras |
| title_fullStr | Real-time dense simultaneous localization and mapping using monocular cameras |
| title_full_unstemmed | Real-time dense simultaneous localization and mapping using monocular cameras |
| title_short | Real-time dense simultaneous localization and mapping using monocular cameras |
| title_sort | real time dense simultaneous localization and mapping using monocular cameras |
| topic | Aeronautics and Astronautics. |
| url | http://hdl.handle.net/1721.1/107051 |
| work_keys_str_mv | AT greenewnicholaswilliamnicholas realtimedensesimultaneouslocalizationandmappingusingmonocularcameras |